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Traffic in urban areas is an important source of greenhouse gas (GHG) and air pollutant emissions. Estimating traffic-related emissions is therefore a key component in compiling a city emission inventory. Inventories are fundamental for understanding, monitoring, managing, and mitigating local pollutant emissions. We present DRIVE v1.0, a data-driven framework to calculate road transport emissions based on a multi-modal macroscopic traffic model, vehicle class-specific traffic counting data from more than a hundred counting stations, and HBEFA emission factors. DRIVE introduces a novel approach for estimating traffic emissions with vehicle-specific temporal profiles in hourly resolution. In addition, we use traffic counting data to estimate the uncertainty of traffic activity and the resulting emission estimates at different temporal aggregation levels and with road link resolution. The framework was applied to the City of Munich, covering an area of 311 km2 and accounting for GHGs (CO2, CH4) and air pollutants (PM, CO, NOx). It captures irregular events such as COVID lockdowns and holiday periods well and is suitable for use in near real-time applications. Emission estimates for 2019–2022 are presented and differences in city totals and spatial distribution compared to the official municipal reported and national and European downscaled inventories are examined.

Urban areas are major contributors to anthropogenic CO.sub.2 emissions, yet detailed monitoring remains a challenge due to the cost and operational constraints of traditional sensor networks. As a scalable alternative, we established the ACROPOLIS (Autonomous and Calibrated Rooftop Observatory for MetroPOLItan Sensing) network in the Munich metropolitan area, using mid-cost sensors to enable dense, city-scale observation. This work outlines the development of the hardware and software of the system, its performance and the first 1.5 years of operation, during which more than 90 million CO.sub.2 measurements were collected in urban, suburban and rural environments.

Urban areas are major contributors to anthropogenic CO2 emissions, yet detailed monitoring remains a challenge due to the cost and operational constraints of traditional sensor networks. As a scalable alternative, we established the ACROPOLIS (Autonomous and Calibrated Rooftop Observatory for MetroPOLItan Sensing) network in the Munich metropolitan area, using mid-cost sensors to enable dense, city-scale observation. This work outlines the development of the hardware and software of the system, its performance and the first 1.5 years of operation, during which more than 90 million CO2 measurements were collected in urban, suburban and rural environments. The primary goal was to evaluate whether mid-cost Vaisala GMP343 sensors, when combined with manufacturer internal corrections and environmental stabilization, can reliably measure CO2 concentrations with sufficient accuracy to resolve urban gradients. We implemented a fully automated 2-point calibration procedure using synthetic dry reference gases and conducted a multi-week side-by-side comparison with a high-precision Picarro reference instrument to assess sensor performance. Our results show that, despite inter-sensor variability in temperature sensitivity, the hourly aggregated mean root mean square error (RMSE) of all sensors is 1.16 ppm with a range of 0.57 to 2.58 ppm. For the specific sensor housed in our second-generation enclosure with PID-controlled heating, the performance improved from 0.9 to 0.6 ppm RMSE. Analysis of spatial and temporal patterns reveal distinct seasonal cycles, urban–rural concentration gradients, and nighttime accumulation events, consistent with expected biogenic and anthropogenic activity, and atmospheric transport mechanisms. We conclude that mid-cost urban networks can provide scientifically valuable, spatially highly resolved greenhouse gas observations when supported by appropriate calibration and stabilization techniques. The open-source design and demonstrated performance of the ACROPOLIS network establish a blueprint for future deployments in other cities seeking to advance emissions monitoring and urban climate policy.

For nearly 3 decades, listeriologists and immunologists have used mainly three strains of the same serovar (1/2a) to analyze the virulence of the bacterial pathogen Listeria monocytogenes . The genomes of two of these strains, EGD-e and 10403S, were released in 2001 and 2008, respectively. Here we report the genome sequence of the third reference strain, EGD, and extensive genomic and phenotypic comparisons of the three strains. Strikingly, EGD-e is genetically highly distinct from EGD (29,016 single nucleotide polymorphisms [SNPs]) and 10403S (30,296 SNPs), and is more related to serovar 1/2c than 1/2a strains. We also found that while EGD and 10403S strains are genetically very close (317 SNPs), EGD has a point mutation in the transcriptional regulator PrfA (PrfA*), leading to constitutive expression of several major virulence genes. We generated an EGD-e PrfA* mutant and showed that EGD behaves like this strain in vitro , with slower growth in broth and higher invasiveness in human cells than those of EGD-e and 10403S. In contrast, bacterial counts in blood, liver, and spleen during infection in mice revealed that EGD and 10403S are less virulent than EGD-e, which is itself less virulent than EGD-e PrfA*. Thus, constitutive expression of PrfA-regulated virulence genes does not appear to provide a significant advantage to the EGD strain during infection in vivo , highlighting the fact that in vitro invasion assays are not sufficient for evaluating the pathogenic potential of L. monocytogenes strains. Together, our results pave the way for deciphering unexplained differences or discrepancies in experiments using different L. monocytogenes strains. IMPORTANCE Over the past 3 decades, Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields, including bacterial gene regulation, cell biology, and bacterial pathophysiology. Scientists studying Listeria use primarily three pathogenic strains: EGD, EGD-e, and 10403S. Despite many studies on EGD, it is the only one of the three strains whose genome has not been sequenced. Here we report the sequence of its genome and a series of important genomic and phenotypic differences between the three strains, in particular, a critical mutation in EGD’s PrfA, the main regulator of Listeria virulence. Our results show that the three strains display differences which may play an important role in the virulence differences observed between the strains. Our findings will be of critical relevance to listeriologists and immunologists who have used or may use Listeria as a tool to study the pathophysiology of listeriosis and immune responses. Over the past 3 decades, Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields, including bacterial gene regulation, cell biology, and bacterial pathophysiology. Scientists studying Listeria use primarily three pathogenic strains: EGD, EGD-e, and 10403S. Despite many studies on EGD, it is the only one of the three strains whose genome has not been sequenced. Here we report the sequence of its genome and a series of important genomic and phenotypic differences between the three strains, in particular, a critical mutation in EGD’s PrfA, the main regulator of Listeria virulence. Our results show that the three strains display differences which may play an important role in the virulence differences observed between the strains. Our findings will be of critical relevance to listeriologists and immunologists who have used or may use Listeria as a tool to study the pathophysiology of listeriosis and immune responses.

For nearly 3 decades, listeriologists and immunologists have used mainly three strains of the same serovar (1/2a) to analyze the virulence of the bacterial pathogen Listeria monocytogenes. The genomes of two of these strains, EGD-e and 10403S, were released in 2001 and 2008, respectively. Here we report the genome sequence of the third reference strain, EGD, and extensive genomic and phenotypic comparisons of the three strains. Strikingly, EGD-e is genetically highly distinct from EGD (29,016 single nucleotide polymorphisms [SNPs]) and 10403S (30,296 SNPs), and is more related to serovar 1/2c than 1/2a strains. We also found that while EGD and 10403S strains are genetically very close (317 SNPs), EGD has a point mutation in the transcriptional regulator PrfA (PrfA*), leading to constitutive expression of several major virulence genes. We generated an EGD-e PrfA* mutant and showed that EGD behaves like this strain in vitro, with slower growth in broth and higher invasiveness in human cells than those of EGD-e and 10403S. In contrast, bacterial counts in blood, liver, and spleen during infection in mice revealed that EGD and 10403S are less virulent than EGD-e, which is itself less virulent than EGD-e PrfA*. Thus, constitutive expression of PrfA-regulated virulence genes does not appear to provide a significant advantage to the EGD strain during infection in vivo, highlighting the fact that in vitro invasion assays are not sufficient for evaluating the pathogenic potential of L. monocytogenes strains. Together, our results pave the way for deciphering unexplained differences or discrepancies in experiments using different L. monocytogenes strains. IMPORTANCE Over the past 3 decades, Listeria has become a model organism for host-pathogen interactions, leading to critical discoveries in a broad range of fields, including bacterial gene regulation, cell biology, and bacterial pathophysiology. Scientists studying Listeria use primarily three pathogenic strains: EGD, EGD-e, and 10403S. Despite many studies on EGD, it is the only one of the three strains whose genome has not been sequenced. Here we report the sequence of its genome and a series of important genomic and phenotypic differences between the three strains, in particular, a critical mutation in EGD's PrfA, the main regulator of Listeria virulence. Our results show that the three strains display differences which may play an important role in the virulence differences observed between the strains. Our findings will be of critical relevance to listeriologists and immunologists who have used or may use Listeria as a tool to study the pathophysiology of listeriosis and immune responses.